Learning on your own sucks, so we won’t do that to you. Each course will have a cohort of students working through the content together — watch lectures at your own pace, and join, and will mix together self-led lectures with synchronous tutorials (the flipped-classroom model, for any education buffs out there!)
You’ll use relevant datasets, real tools, and learn to solve problems experienced by data teams every day. No iris or titanic datasets, and no web-based IDEs.
Taught by experts
Search for the term “analytics engineer”, and it won’t take you long to find content written by our founding team, Michael Kaminsky and Claire Carroll. Between the two of us we’ve:
- Been members of data team
- Run data teams
- Built leading data communities
- Mentored dozens of analytics engineers
- Trained hundreds of analytics engineers
- Written technical content used by thousands of people every month
So it’s safe to say — we know what we’re talking about.
Meet the instructors
As the sole analyst at a fast-growing startup, Claire experienced the pain of the traditional analyst workflow — an ever-growing backlog of requests, and numbers that never quite matched up. So she taught herself dbt, the command line, version control and brought all the rigor of analytics engineering to her team.
After realizing the impact that an analytics engineering mindset could have on an analyst’s career, Claire took on a role growing the dbt community, bringing analytics engineering to thousands of data analysts and engineers.
Michael has worked as an economist, statistician, analyst, data scientist, but analytics engineering will always hold a special place in his heart. Michael built one of the world’s first analytics engineering teams while leading the data team at online-razor-startup-turned-CPG-goliath Harry’s and has written extensively about the practice as a founding leader of the Locally Optimistic blog and community.
Applications for our current cohort are currently closed. Join our mailing list and we’ll keep you up to date about new cohorts as we open applications.
Part time — we expect that students will spend around 5 hours a week completing coursework. Lessons will be a mix of asynchronous learning (videos, written content, and self-led exercises) and collaborative learning (with instructors, over Zoom) .
This course is designed for students who are currently employed as data analysts:
✅ You can write the SQL to calculate the monthly revenue of a business (given an orders table), though you’d like some feedback on the best way to write that SQL
✅ You’re comfortable with the terms “table”, “view” and “schema” in a database (though perhaps the differences between a table and view are a little blurry)
✅ Your company is supporting you in taking this next step
This course is not for you if you’re already comfortable using git, dbt, and writing small python scripts — we hope to offer more advanced courses in the future for students in this category.
That’s not a question! But that is something we’re interested in. Drop us an email, and we’ll get in touch.
Recent blog articles we’ve written
What’s a DAG?
Teaching the Real Tools